What is Active and Passive ONA (Organizational Network Analysis)

ONA (Organizational Network Analysis) is an analytical method that makes the information flow and collaboration networks within an organization visible. This analysis helps to understand real interactions and business relationships, going beyond classical hierarchical structures.

What is Active ONA?

Active ONA refers to the data collection on collaboration structures through surveys sent to employees. This method directly analyzes how and with whom employees collaborate over a specific time frame based on participant feedback.

What is Passive ONA?

Passive ONA analyzes data obtained from digital collaboration tools such as email, calendars, Microsoft Teams, Zoom, and Slack. Thanks to the continuous data flow, interaction patterns within the organization emerge in a more natural and real-time manner.

📊 Modern analytical tools like Inboxage provide more comprehensive and accurate insights by integrating both active and passive ONA data. Inboxage only examines interaction patterns; it does not analyze information that could violate privacy, such as email contents or subject lines.

In What Areas is ONA Used?

Visual 2: Examples of ONA use cases (Source: David Green)

ONA is widely used in Human Resources Analytics (HR Analytics) and organizational development processes. It is particularly valuable when seeking answers to the following questions:

• How are teams collaborating?

• What is the relationship between performance and behaviors?

• Who are the most contributing employees?

• What is the level of inter-departmental communication?

• What is the situation of burnout risk within the organization?

• How are employees with leadership potential (HIPO) identified?

• What is the effect of demographic factors (age, gender, tenure, etc.) on business decisions?

Why Should You Use ONA?

ONA sheds light on questions that traditional analytical methods cannot answer and offers the following values:

• Statistical performance indicators

• Inter-departmental comparisons

• Early detection of burnout risk

• Strategic talent management

• Data-driven approaches in decision-making processes

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